2) Download the puppy\'s image Convert it to grayscale. Let me lenoefyou prfer t

Question

2) Download the puppy's image Convert it to grayscale. Let me lenoefyou prfer to work with a different ma Find te dynamc rare, of you mee That age between madman me)) and min mname)Create a random noise matrix of the same sie: andn iv facton Use help to learn about r your signal dynamic range Scalethenome to be approumately 10%of V Add the noise to the image. Display the original image and the noisy image side by side vi Create the Sollowing b. 10 point moving Rget c. Fint dfference filter e. Twe dimensional filter be-125,-1, 25,-1,3,-1;25,-1,25 g. In case ofone dimensaon fileron) explan what the fiber effect is on Fiher with the following coeficints [101 Sobel Filtef with eotiesett"-[121,000,-1-2.1k the image. For example is the image sharper or bhary What is the size of new mer. Descr be if the filter hagh-low orbanpas by observing the outpur? Can you point to the transient part of the image? Use a curvor and determine the nuember of points in the transient respoese of the filter Display the magnitude of the system function of each fiher. Rellate this observation to your answer in part Cases e and fare 2 dimensional filtes Each ier kernel must be uniquely pphed to he signal using fiher2 and the same in the command line. Explain nyour own words the role ofthe·ame and why necessary Doagoogle sewch to learn what a 'Sobel fher xCode to calculate the R3ES esror between the Eihered signals (a bra d) and the oniginal signal and deterine which one is the closest to the oniginal bw image mage Desagmadre hold detectorfher to "incor elementaslithenegative of detect the eyes and the nose x

Explanation / Answer

MATLAB CODE:

Im=imread('puppy.jpeg');

figure,imshow(Im);
title('Original Image');

%0.2989 * R + 0.5870 * G + 0.1140 * B
GIm=uint8(zeros(size(Im,1),size(Im,2)));
for i=1:size(Im,1)
for j=1:size(Im,2)
GIm(i,j)=0.2989*Im(i,j,1)+0.5870*Im(i,j,2)+0.1140*Im(i,j,3);
end
end

%Without using for loop:
%GIm=0.2989*Im(:,:,1)+0.5870*Im(:,:,2)+0.1140*Im(:,:,3);

figure,imshow(GIm);
title('Grayscale Image');

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